Identifying tree health using sentinel-2 images: a case study on Tortrix viridana L. infected oak trees in Western Iran-Reference-Cited by-同舟云学术

Identifying tree health using sentinel-2 images: a case study on Tortrix viridana L. infected oak trees in Western Iran

Published:2020-01-29 Issue:1 Volume:37 Page:304-314
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Haghighian Farshad¹,Yousefi Saleh²^ORCID,Keesstra Saskia³⁴^ORCID

Affiliation:

1. Research Division of Natural Resources, Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center, AREEO, Shahrekord, Iran

2. Soil Conservation and Watershed Management Research Department, Chaharmahal and Bakhtiari Agricultural and Natural Resources Research and Education Center, AREEO, Shahrekord, Iran

3. Soil, Water and Land Use Team, Wageningen Environmental Research, Wageningen UR, Wageningen, The Netherlands

4. Civil, Surveying and Environmental Engineering, The University of Newcastle, Callaghan, Australia

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2020.1716397

Reference67 articles.

1. Space-time dynamics of deforestation in Brazilian Amazônia

2. Roads, deforestation, and the mitigating effect of protected areas in the Amazon

3. Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting canopy chlorophyll concentration in citronella crop using machine learning algorithms and spectral vegetation indices derived from UAV multispectral imagery;Industrial Crops and Products;2024-11

2. A systematic review of the application of remote sensing technologies in mapping forest insect pests and diseases at a tree-level;Remote Sensing Applications: Society and Environment;2024-11

3. Monitoring and prediction of the spongy moth (Lymantria dispar) outbreaks in Mountain’s landscape using a combination of Sentinel-2 images and nonlinear time series model;Forest Ecology and Management;2024-07

4. Integration of satellite remote sensing and MaxEnt modeling for improved detection and management of forest pests;Environmental Monitoring and Assessment;2024-06-14

5. Evaluating an Innovative ICT System for Monitoring Small-Scale Forest Operations: Preliminary Tests in Mediterranean Oak Coppices;Sustainability;2024-05-29